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Using a Real-Time Locating System to Measure Walking Activity Associated with Wandering Behaviors Among Institutionalized Older Adults

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A Mobility Aware Binary Tree Algorithm to Resolve RFID Jam and Bottleneck Problems in a Next Generation Specimen

Yen-Hung Chen¹, Yen-An Chen², Shu-Rong Huang³

¹Department of Information Management, National Taipei University of Nursing and Health Sciences, Taipei 112, Taiwan.

|August 8, 2020

Summary

This study introduces a new RFID algorithm (MABT) to improve specimen tracking in hospitals. It addresses dynamic arrival rates, reducing delays and errors in clinical laboratory transfers.

Keywords:

RFID anti-collision mobile tag specimen management tag identification

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Area of Science:

Biomedical Engineering
Laboratory Automation
Supply Chain Management

Background:

Hospitals face challenges with delayed analysis and specimen errors during transfers.
Radio-frequency identification (RFID) offers automated labeling and tracking to reduce costs and delays.
Existing RFID solutions struggle with dynamic specimen arrival rates, causing bottlenecks.

Purpose of the Study:

To propose a novel RFID anti-collision algorithm to enhance specimen identification.
To address the limitations of conventional RFID algorithms in dynamic environments.
To improve the efficiency of specimen tracking in hospital logistics.

Main Methods:

Development of the Mobility Aware Binary Tree Algorithm (MABT).
Focus on optimizing tag identification under dynamic arrival rates.
Consideration of reader coverage area and limited dwell time.

Main Results:

MABT improves the identification of dynamic tags within RFID reader range.
The algorithm is designed to handle fluctuating specimen arrival rates effectively.
Potential to reduce bottlenecks and improve overall laboratory workflow.

Conclusions:

The proposed MABT algorithm offers a significant improvement over existing RFID methods for specimen tracking.
It provides a practical solution for real-world hospital laboratory environments with dynamic workflows.
MABT can contribute to reducing errors and analytic delays in clinical settings.